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Alert Now or Never: Understanding and Predicting Notification Preferences of Smartphone Users.

Authors :
TIANSHI LI
HAINES, JULIA KATHERINE
RUIZ DE EGUINO, MIGUEL FLORES
HONG, JASON I.
NICHOLS, JEFFREY
Source :
ACM Transactions on Computer-Human Interaction (TOCHI); Oct2022, Vol. 29 Issue 5, p1-33, 33p
Publication Year :
2022

Abstract

Notifications are an indispensable feature of mobile devices, but their delivery can interrupt and distract users. Prior work has examined interventions, such as deferring notification delivery to opportune moments, but has not systematically studied how users might prefer an intelligent system to manage their notifications. Hence, we directly probed Android smartphone users' notification preferences via a one-week experiencesampling study (N = 35). We found that users prefer mitigating undesired interruptions by suppressing alerts over deferring them and referred to notification content factors more frequently than contextual factors for explaining their preferences. Then we demonstrated the challenges and potentials of leveraging user actions to help predict notification preferences. Specifically, we showed that a model personalized using user actions achieved a performance gain of 39% than a generic model. This improvement is similar to the 42% performance gain using labels solicited from the user while using observable user actions causes no extra disruption. [ABSTRACT FROM AUTHOR]

Subjects

Subjects :
FORECASTING

Details

Language :
English
ISSN :
10730516
Volume :
29
Issue :
5
Database :
Complementary Index
Journal :
ACM Transactions on Computer-Human Interaction (TOCHI)
Publication Type :
Academic Journal
Accession number :
161240160
Full Text :
https://doi.org/10.1145/3478868